Qi Liao

Large-scale prediction of long non-coding RNA functions in a coding–non-coding gene co-expression network

Although accumulating evidence has provided insight into the various functions of long-non-coding RNAs (lncRNAs), the exact functions of the majority of such transcripts are still unknown. Here, we report the first computational annotation of lncRNA functions based on public microarray expression profiles. A coding–non-coding gene co-expression (CNC) network was constructed from re-annotated Affymetrix Mouse Genome Array data. Probable functions for altogether 340 lncRNAs were predicted based on topological or other network characteristics, such as module sharing, association with network hubs and combinations of co-expression and genomic adjacency. The functions annotated to the lncRNAs mainly involve organ or tissue development (e.g. neuron, eye and muscle development), cellular transport (e.g. neuronal transport and sodium ion, acid or lipid transport) or metabolic processes (e.g. involving macromolecules, phosphocreatine and tyrosine).

NONCODE v3.0: integrative annotation of long noncoding RNAs

Facilitated by the rapid progress of high-throughput sequencing technology, a large number of long noncoding RNAs (lncRNAs) have been identified in mammalian transcriptomes over the past few years. LncRNAs have been shown to play key roles in various biological processes such as imprinting control, circuitry controlling pluripotency and differentiation, immune responses and chromosome dynamics. Notably, a growing number of lncRNAs have been implicated in disease etiology. With the increasing number of published lncRNA studies, the experimental data on lncRNAs (e.g. expression profiles, molecular features and biological functions) have accumulated rapidly. In order to enable a systematic compilation and integration of this information, we have updated the NONCODE database (http://www.noncode.org) to version 3.0 to include the first integrated collection of expression and functional lncRNA data obtained from re-annotated microarray studies in a single database. NONCODE has a user-friendly interface with a variety of search or browse options, a local Genome Browser for visualization and a BLAST server for sequence-alignment search. In addition, NONCODE provides a platform for the ongoing collation of ncRNAs reported in the literature. All data in NONCODE are open to users, and can be downloaded through the website or obtained through the SOAP API and DAS services.

Mammalian target of rapamycin regulates murine and human cell differentiation through STAT3/p63/Jagged/Notch cascade

The receptor tyrosine kinase/PI3K/AKT/mammalian target of rapamycin (RTK/PI3K/AKT/mTOR) pathway is frequently altered in cancer, but the underlying mechanism leading to tumorigenesis by activated mTOR remains less clear. Here we show that mTOR is a positive regulator of Notch signaling in mouse and human cells, acting through induction of the STAT3/p63/Jagged signaling cascade. Furthermore, in response to differential cues from mTOR, we found that Notch served as a molecular switch to shift the balance between cell proliferation and differentiation. We determined that hyperactive mTOR signaling impaired cell differentiation of murine embryonic fibroblasts via potentiation of Notch signaling. Elevated mTOR signaling strongly correlated with enhanced Notch signaling in poorly differentiated but not in well-differentiated human breast cancers. Both human lung lymphangioleiomyomatosis (LAM) and mouse kidney tumors with hyperactive mTOR due to tumor suppressor TSC1 or TSC2 deficiency exhibited enhanced STAT3/p63/Notch signaling. Furthermore, tumorigenic potential of cells with uncontrolled mTOR signaling was suppressed by Notch inhibition. Our data therefore suggest that perturbation of cell differentiation by augmented Notch signaling might be responsible for the underdifferentiated phenotype displayed by certain tumors with an aberrantly activated RTK/PI3K/AKT/mTOR pathway. Additionally, the STAT3/p63/Notch axis may be a useful target for the treatment of cancers exhibiting hyperactive mTOR signaling.

Long non-coding RNAs function annotation: a global prediction method based on bi-colored networks

More and more evidences demonstrate that the long non-coding RNAs (lncRNAs) play many key roles in diverse biological processes. There is a critical need to annotate the functions of increasing available lncRNAs. In this article, we try to apply a global network-based strategy to tackle this issue for the first time. We develop a bi-colored network based global function predictor, long non-coding RNA global function predictor (‘lnc-GFP’), to predict probable functions for lncRNAs at large scale by integrating gene expression data and protein interaction data. The performance of lnc-GFP is evaluated on protein-coding and lncRNA genes. Cross-validation tests on protein-coding genes with known function annotations indicate that our method can achieve a precision up to 95%, with a suitable parameter setting. Among the 1713 lncRNAs in the bi-colored network, the 1625 (94.9%) lncRNAs in the maximum connected component are all functionally characterized. For the lncRNAs expressed in mouse embryo stem cells and neuronal cells, the inferred putative functions by our method highly match those in the known literature.

ncFANs: a web server for functional annotation of long non-coding RNAs

Recent interest in the non-coding transcriptome has resulted in the identification of large numbers of long non-coding RNAs (lncRNAs) in mammalian genomes, most of which have not been functionally characterized. Computational exploration of the potential functions of these lncRNAs will therefore facilitate further work in this field of research. We have developed a practical and user-friendly web interface called ncFANs (non-coding RNA Function ANnotation server), which is the first web service for functional annotation of human and mouse lncRNAs. On the basis of the re-annotated Affymetrix microarray data, ncFANs provides two alternative strategies for lncRNA functional annotation: one utilizing three aspects of a coding-non-coding gene co-expression (CNC) network, the other identifying condition-related differentially expressed lncRNAs. ncFANs introduces a highly efficient way of re-using the abundant pre-existing microarray data. The present version of ncFANs includes re-annotated CDF files for 10 human and mouse Affymetrix microarrays, and the server will be continuously updated with more re-annotated microarray platforms and lncRNA data. ncFANs is freely accessible at http://www.ebiomed.org/ncFANs/ or http://www.noncode.org/ncFANs/.

Clustered microRNAs' coordination in regulating protein-protein interaction network

BackgroundMicroRNAs (miRNAs), a growing class of small RNAs with crucial regulatory roles at the post-transcriptional level, are usually found to be clustered on chromosomes. However, with the exception of a few individual cases, so far little is known about the functional consequence of this conserved clustering of miRNA loci. In animal genomes such clusters often contain non-homologous miRNA genes. One hypothesis to explain this heterogeneity suggests that clustered miRNAs are functionally related by virtue of co-targeting downstream pathways.ResultsIntegrating of miRNA cluster information with protein protein interaction (PPI) network data, our research supports the hypothesis of the functional coordination of clustered miRNAs and links it to the topological features of miRNAs targets in PPI network. Specifically, our results demonstrate that clustered miRNAs jointly regulate proteins in close proximity of the PPI network. The possibility that two proteins yield to this coordinated regulation is negatively correlated with their distance in PPI network. Guided by the knowledge of this preference, we found several network communities enriched with target genes of miRNA clusters. In addition, our results demonstrate that the variance of this propensity can also partly be explained by proteins connectivity and miRNAs conservation.ConclusionIn summary, this work supports the hypothesis of intra-cluster coordination and investigates the extent of this coordination.

Genome-wide identification and functional annotation of Plasmodium falciparum long noncoding RNAs from RNA-seq data

The life cycle of Plasmodium falciparum is very complex, with an erythrocytic stage that involves the invasion of red blood cells and the survival and growth of the parasite within the host. Over the past several decades, numbers of studies have shown that proteins exported by P. falciparum to the surface of infected red blood cells play a critical role in recognition and interaction with host receptors and are thus essential for the completion of the life cycle of P. falciparum. However, little is known about long noncoding RNAs (lncRNAs). In this study, we designed a computational pipeline to identify new lncRNAs of P. falciparum from published RNA-seq data and analyzed their sequences and expression features. As a result, 164 novel lncRNAs were found. The sequences and expression features of P. falciparum lncRNAs were similar to those of humans and mice: there was a lack of sequence conservation, low expression levels, and high expression coefficient of variance and co-expression with nearby coding sequences in the genome. Next, a coding/noncoding gene co-expression network for P. falciparum was constructed to further annotate the functions of novel and known lncRNAs. In total, the functions of 69 lncRNAs, including 44 novel lncRNAs, were annotated. The main functions of the lncRNAs included metabolic processes, biosynthetic processes, regulation of biological processes, establishment of localization, catabolic processes, cellular component organization, and interspecies interactions between organisms. Our results will provide clues to further the investigation of interactions between human hosts and parasites and the mechanisms of P. falciparum infection.

Systematic study of human long intergenic non-coding RNAs and their impact on cancer

The functional impact of several long intergenic non-coding RNAs (lincRNAs) has been characterized in previous studies. However, it is difficult to identify lincRNAs on a large-scale and to ascertain their functions or predict their structures in laboratory experiments because of the diversity, lack of knowledge and specificity of expression of lincRNAs. Furthermore, although there are a few well-characterized examples of lincRNAs associated with cancers, these are just the tip of the iceberg owing to the complexity of cancer. Here, by combining RNA-Seq data from several kinds of human cell lines with chromatin-state maps and human expressed sequence tags, we successfully identified more than 3000 human lincRNAs, most of which were new ones. Subsequently, we predicted the functions of 105 lincRNAs based on a coding-non-coding gene co-expression network. Finally, we propose a genetic mediator and key regulator model to unveil the subtle relationships between lincRNAs and lung cancer. Twelve lincRNAs may be principal players in lung tumorigenesis. The present study combines large-scale identification and functional prediction of human lincRNAs, and is a pioneering work in characterizing cancer-associated lincRNAs by bioinformatics.

Identifying Schistosoma japonicum Excretory/Secretory Proteins and Their Interactions with Host Immune System

Schistosoma japonicum is a major infectious agent of schistosomiasis. It has been reported that large number of proteins excreted and secreted by S. japonicum during its life cycle are important for its infection and survival in definitive hosts. These proteins can be used as ideal candidates for vaccines or drug targets. In this work, we analyzed the protein sequences of S. japonicum and found that compared with other proteins in S. japonicum, excretory/secretory (ES) proteins are generally longer, more likely to be stable and enzyme, more likely to contain immune-related binding peptides and more likely to be involved in regulation and metabolism processes. Based on the sequence difference between ES and non-ES proteins, we trained a support vector machine (SVM) with much higher accuracy than existing approaches. Using this SVM, we identified 191 new ES proteins in S. japonicum, and further predicted 7 potential interactions between these ES proteins and human immune proteins. Our results are useful to understand the pathogenesis of schistosomiasis and can serve as a new resource for vaccine or drug targets discovery for anti-schistosome.

Dynamic expression of miR-132, miR-212, and miR-146 in the brain of different hosts infected with Angiostrongylus cantonensis

Increasing evidence shows that microRNAs (miRNAs) are a family of regulatory molecules involved in many physiological processes, including the inflammation in central nervous system (CNS) and neurological disorders. Angiostrongylus cantonensis (A. cantonensis) is the major cause of human infectious eosinophilic meningitis and can induce CNS injury. In the present study, we investigated the expression of miRNAs involved in neuronal functions such as miR-132-3p/212-3p, and miR-146a-5p, inflammation-related miRNA, in the modulation of inflammation of CNS of mice and rats induced by A. cantonensis. The functions of differentially expressed miRNAs were analyzed through bioinformatics methods, and the expression of chosen target genes were investigated by quantitative reverse transcription polymerase chain reaction. The results showed that miR-146a-5p upregulated in the brain of rats after 21xa0days; A. cantonensis infection and the expression of miR-132-3p and miR-146a-5p upregulated in the brain of mice model infected by A. cantonensis. The expression of the target genes of mmu-miR-146a-5p such as Irak1 and Traf6 downregulated in 14xa0days and 21xa0days after A. cantonensis infection. Our results supply more information about the involvement of the miRNAs in the regulation of inflammation of CNS induced by A. cantonensis.